What question did this study set out to answer?

The aim is to evaluate whether tumor-educated platelets can predict treatment response in luminal breast cancer through RNA profiling.

February 19, 2026

Abstract PS4-02-03: Tumor-educated platelet RNA captures treatment-induced transcriptomic changes and predicts response in luminal breast cancer

Q: What does this research mean for the field?

Tumor-educated platelet RNA profiling reflects treatment-induced transcriptomic changes and predicts response in luminal breast cancer. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

Key Points

The aim is to evaluate whether tumor-educated platelets can predict treatment response in luminal breast cancer through RNA profiling.
Collected platelet-rich plasma samples at diagnosis, post-neoadjuvant therapy, and post-surgery.
Quantified gene expression of 55 key genes using RT-qPCR.
Analyzed data using PLS-DA, limma for differential expression, and logistic regression for nodal status.
Transcriptomic changes were identified between the different time points in treatment.
A five-gene signature showed excellent accuracy for predicting complete response with an AUC of 0.87.
Certain genes correlated with tumor shrinkage, suggesting their role in response to therapy.

Abstract

Abstract Background: Tumor-educated platelets (TEPs) store cancer-related mRNAs and tolerate routine manipulation, providing a stable and minimally invasive window into disease biology. We wondered whether serial TEPs-RNA profiling reflects therapy-induced changes and predicts response in Luminal (HR+/HER2) breast cancer. Methods: In a prospective luminal cohort (n = 12), platelet-rich plasma was collected at diagnosis (T0), post-neoadjuvant therapy (T1) and post-surgery (TF). Fifty-five immune, proliferative and endocrine genes were quantified by RT-qPCR. Data were analysed with PLS-DA, limma differential expression, Spearman correlation with tumour shrinkage, and logistic regression for nodal status. Results: PLS-DA cleanly separated T0, T1 and TF, indicating stepwise transcriptomic re-programming. Twenty genes differed between T0 vs T1 and T0 vs TF (FDR 0.05); five differed between T1 vs TF. Higher post-neoadjuvant IKBKG and VDR correlated with greater tumour reduction (r ≈ -0.6, p 0.01). A two-gene model (CACNA2D1 + IKBKG) classified axillary involvement with 85% accuracy. A baseline five-gene signature (ADRB2, IL13, CACNA2D1, MET, ERBB2) was identified that distinguishes patients who achieved pathological complete response (pCR), showing an AUC of 0.87 and clear segregation in hierarchical clustering. Enrichment analysis revealed pathways related to cell cycle control, DNA repair, and p53 regulation, highlighting biological processes associated with treatment response. Conclusions: Sequential TEPs-RNA profiling reflects molecular effects of therapy and surgery and yields baseline biomarkers of complete response in luminal breast cancer. Platelet RNA warrants prospective validation as an accessible complement to tissue-based assays for personalized treatment. Citation Format: I. URDANIBIA, A. VELASCO, G. RODRIGUEZ, N. TUSET, A. GASOL, S. MORALES. Tumor-educated platelet RNA captures treatment-induced transcriptomic changes and predicts response in luminal breast cancer. abstract. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS4-02-03.

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Abstract PS4-02-03: Tumor-educated platelet RNA captures treatment-induced transcriptomic changes and predicts response in luminal breast cancer

Key Points

Abstract

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